Senior Staff AI Platform Engineer

Our Purpose At SentinelOne, we are driven by a clear purpose: to give the advantage to those who secure our future. As AI reshapes how organizations build, operate, and innovate, the responsibility to protect them becomes more critical than ever. When you join SentinelOne, your work helps protect global enterprises, critical infrastructure, and the technologies shaping tomorrow. If you are motivated by meaningful challenges and want your impact to be real, measurable, and global, you will find purpose here. About Us SentinelOne is a company at the intersection of AI and security, pioneering a new operating model for cybersecurity. Our AI-native platform unifies protection across endpoint, cloud, identity, data, and AI systems to deliver autonomous detection and response with clarity and speed. By combining real-time analytics, intelligent automation, and a unified data foundation, we reduce noise, simplify complexity, and empower security teams to focus on what truly matters. Our teams are builders, problem-solvers, and innovators committed to shaping the future of security. If you are excited to solve hard problems alongside talented, mission-driven people, we invite you to help us build a safer future for humanity. What Are We Looking For? We’re looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes. As a Senior Staff AI Platform Engineer, you will be tasked with serving as a hands-on builder of SentinelOne's enterprise AI platform, including the Gateway, Harness, and Semantic Layers that every internal AI use case runs on top of. You will write the production code that governs, observes, secures, and scales AI activity across the company, working closely with the Sr. Director of Enterprise AI Platform Engineering and the rest of the platform team to take the architecture from design into running infrastructure. What Will You Do? Primary responsibilities include: Design, build, and operate secure, scalable cloud infrastructure supporting Enterprise AI Platform services across Google Cloud Platform (GCP) and AWS. Build and operate Kubernetes-based runtime environments for platform services, APIs, gateways, agents, and supporting infrastructure. Develop reusable Infrastructure as Code using Terraform or equivalent tooling for cloud resources, networking, IAM, Kubernetes, and shared platform dependencies. Build and maintain CI/CD and GitOps workflows that enable consistent build, test, promotion, deployment, and rollback across environments. Create standardized deployment patterns and self-service platform capabilities that reduce friction for engineering teams. Own Kong Gateway as a core Enterprise AI Platform capability, including deployment, upgrades, scaling, ingress and routing, authentication and authorization integrations, rate limiting, traffic policies, plugins, observability, and lifecycle management. Establish reusable automation and standards for onboarding and managing APIs through Kong Gateway, including configuration management, environment promotion, versioning, rollback, and policy enforcement. Partner with Infosec and engineering teams to implement least-privilege access, workload identity, secrets management, policy enforcement, and secure software supply-chain practices. Build and evolve platform observability, including metrics, logging, distributed tracing, dashboards, alerting, SLOs, and auditability. Improve platform reliability through autoscaling, health checks, failover, capacity planning, operational automation, and incident remediation. Support the infrastructure needs of AI Gateway, model routing, agent orchestration, MCP services, semantic and vector services, and other AI platform capabilities. Write clear technical documentation and participate in architecture, infrastructure, and code reviews, maintaining a high bar for reliability, security, automation, and maintainability. Partner with Enterprise Data, Enterprise Apps, Product Development, Infosec, and other infrastructure teams to establish shared platform standards and architectural contracts. What Skills and Knowledge Will You Bring? Ideal candidates will have: 8 or more years of professional engineering experience, with significant experience in platform engineering, cloud infrastructure, DevOps, SRE, or production infrastructure. Strong hands-on experience with Google Cloud Platform (GCP) preferred, including networking, IAM, compute, storage, managed services, and production operations; comparable AWS experience is also valuable. Deep practical experience with Kubernetes in production, including deployments, services, ingress, autoscaling, resource management, security, and troubleshooting. Strong Infrastructure as Code experience, preferably Terraform, including reusable modules and multi-environment infrastructure management. Hands-on experience with modern CI/CD and GitOps tooling such as GitHub Actions, Argo CD, GitLab CI, Jenkins, or equivalent. Strong understanding of cloud networking, private connectivity, DNS, load balancing, ingress, proxies, firewalls, and API gateway architectures. Strong hands-on experience operating Kong Gateway, Kong Ingress Controller, or comparable API gateway technologies in production. Experience managing API gateway lifecycle and policy controls, including routing, authentication, authorization, rate limiting, plugins, upgrades, configuration, and rollback strategies. Experience implementing secure platform infrastructure using IAM, workload identity, RBAC, secrets management, encryption, policy-as-code, and least-privilege access patterns. Strong experience with o